Journal
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Volume 50, Issue 10, Pages 4173-4184Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2012.2189011
Keywords
Covariance descriptor; feature extraction; high-resolution synthetic aperture radar (SAR); ship detection; ship discrimination; subaperture analysis
Categories
Funding
- National Natural Science Foundation of China [60901067]
- Program for New Century Excellent Talents in University [NCET-09-0630]
- Program for Changjiang Scholars and Innovative Research Team in University [IRT0954]
- Fundamental Research Funds for the Central Universities
Ask authors/readers for more resources
This paper presents a new hierarchical scheme for detecting ships from high-resolution synthetic aperture radar (SAR) images. The scheme consists of two stages: detection and discrimination. In the detection stage, the existing internal Hermitian product is extended to obtain a new detector. The new detector makes a combined use of the complex coherence among more than two subapertures and the intensity of each subaperture. When the subaperture number is increased, the target/clutter contrast is shown to be improved. Ship candidates are obtained by applying a threshold. Ship discrimination is performed by using one-class classification. The covariance descriptor, developed by Tuzel et al. in 2006, is introduced to SAR ship discrimination as the feature. The traditional one-class quadratic discriminator is used as the discriminator. After this stage, most false alarms are rejected, and the real ship targets in the candidates are maintained. The effectiveness of the proposed scheme is verified using RADARSAT-2 data. Experimental results show that the proposed scheme can detect most ship targets in the image and few false alarms occur.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available